The candidate is a genetic statistician in the Department of Biostatistics at Yale School of Public Health. Her research interests focus on the development and applications of statistical methods and computational algorithms for understanding the vulnerability and progression of addiction behaviors, from a genetic perspective. This K01 Award is designed to provide the candidate with the support necessary to accomplish the following goals: (1) to establish a more in-depth understanding of alcoholism and its clinical manifestations; (2) to gain knowledge on the characteristics of alcohol use in HIV infected population; (3) to increase her proficiency in psychiatric genetics; (4) to advance her skills in statistical modeling and computation; and (5) to develop an independent research program in the interface of statistics, genetics and psychiatry. To achieve these goals, the candidate has assembled a multi-disciplinary mentoring team comprised of a primary mentor, Dr. Hongyu Zhao, Chair of the Biostatistics Department at Yale, an expert in statistical genetics, computational biology and human genetics, and three co-mentors: Dr. Joel Gelernter, who has expertise in the genetics of psychiatric disorders; Dr. John Krystal, a pioneer in the application of translational neuroscience approaches to the study of alcoholism; and Dr. Amy Justice, an expert on outcome research in chronic HIV infection. Alcohol use disorder is a predominant problem in HIV infected population. The proposed research in this application is to improve the detection of genes and gene-environment interactions by developing novel statistical methods making better use of the longitudinal genetic data. The proposed methods will be used to characterize the course of alcohol exposure in the Veterans Aging Cohort Study (VACS). In this study, a series of kernel- machine nonparametric methods will be developed and applied to a genome-wide study to (1) search for the joint genetic effects at various levels of biological information such as genes, regions and pathways; (2) detect genes affecting the temporal patterns of alcohol use; and (3) explore GE interactions with social- environmental factors (e.g., marital status, homelessness and employment) that are well established correlated of alcohol related problems, and potential GHIV interactions in the course of alcohol use. The novel genetic and environmental interaction findings will likely provide new insights into the etiology of alcohol use disorder, particularly in HIV infected population. The training and research experience gained from the proposed study will serve as the groundwork for an independent research program with a focus on methodological work to help understand the genetic and environmental mechanisms underlying alcohol use and comorbid disorders.